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DBMS > Amazon Neptune vs. Cubrid vs. Databricks vs. Datomic

System Properties Comparison Amazon Neptune vs. Cubrid vs. Databricks vs. Datomic

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCubrid  Xexclude from comparisonDatabricks  Xexclude from comparisonDatomic  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Websiteaws.amazon.com/­neptunecubrid.com (korean)
cubrid.org (english)
www.databricks.comwww.datomic.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcescubrid.org/­manualsdocs.databricks.comdocs.datomic.com
DeveloperAmazonCUBRID Corporation, CUBRID FoundationDatabricksCognitect
Initial release2017200820132012
Current release11.0, January 20211.0.6735, June 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial infolimited edition free
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++, JavaJava, Clojure
Server operating systemshostedLinux
Windows
hostedAll OS with a Java VM
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyesno
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyeswith Databricks SQLno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Python
R
Scala
Clojure
Java
Server-side scripts infoStored proceduresnoJava Stored Proceduresuser defined functions and aggregatesyes infoTransaction Functions
TriggersnoyesBy using transaction functions
Partitioning methods infoMethods for storing different data on different nodesnonenonenone infoBut extensive use of caching in the application peers
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.Source-replica replicationyesnone infoBut extensive use of caching in the application peers
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes inforecommended only for testing and development
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardno
More information provided by the system vendor
Amazon NeptuneCubridDatabricksDatomic
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon NeptuneCubridDatabricksDatomic
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